Biostatistics in the Pharmaceutical Industry

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Pharmaceutical companies are subject to a ... FDA to require drug companies to conduct and submit ... statistical analysis should be clearly specified in a.
- Katherine L. Stern M.S. Statistical Sciences Allergan, Inc. Global Drug Development, Director, Global Clinical Quality and Training March 2012

Thank you to my teachers Mrs. Gurley, Dan D. Rogers Elementary, Dallas, TX  Mrs. Neal, The Hockaday School, Dallas, TX  Dr. Patricia Daniel, SMU, Dallas, TX  Dr. Robert Davis, SMU, Dallas, TX  Dr. Donald Owen, SMU, Dallas, TX 

Presentation to Dr. Lee Kucera’s AP Statistics Class Capistrano Valley High School, Mission Viejo, CA  June 2010  FDA History: http://www.fda.gov/AboutFDA/WhatWeDo/Hi story/default.htm 

Some Reasons to Be a Statistician  Deviation is considered normal.  We only need to be right 95% of the time.  We many not be normal but we are transformable.  We never have to say we are certain.

....  No one wants our jobs. 

Statistics are Everywhere  Understand results  Decide if statistical methods were appropriate and used properly  Decide if principles of experimental design were employed

What is Biostatistics? Biostatistics is the application of statistics in the development and use of therapeutic drugs and devices in humans and animals.

 Statisticians often use the method of

comparison.  We want to know the effect of a treatment (like the Salk vaccine) on a response (like getting polio).  Compare the responses of a treatment group with a control group.

Pharmaceutical Industry  The pharmaceutical industry develops,

produces, and markets drugs that are licensed for use as medications.

 Pharmaceutical companies are subject to a

variety of laws and regulations regarding the patenting, testing and marketing of drugs.

FDA = Food and Drug Administration  The FDA is responsible for protecting the

public health by assuring the safety, effectiveness, and security of human and veterinary drugs, vaccines and other biological products, medical devices, our nation’s food supply, cosmetics, dietary supplements, and products that give off radiation.

FDA  FDA’s responsibilities extend to the 50 United States,

the District of Columbia, Puerto Rico, Guam, the Virgin Islands, American Samoa, and other U.S. territories and possessions.

Bureau of Chemistry  1862 President Lincoln appointed a chemist, Charles

M. Wetherill, to serve in the new Department of Agriculture. This was the beginning of the Bureau of Chemistry, the predecessor of the Food and Drug Administration.

Medicine men competed with the circuses, the minstrel shows, and "wild west" performers to entertain the public -- and sell their products. For minor aches and pains, this liniment continued to be sold for many years after the shows had ceased.

 Medicines containing such drugs as opium,

morphine, heroin, and cocaine were sold without restriction. Labeling gave no hint of their presence.  Otherwise harmless preparations were labeled for the cure of every disease and symptom.  Labels did not list ingredients.  What information the public received came frequently from bitter experience.

 In 1906, Upton Sinclair’s book The Jungle

described the filthy conditions of a Chicago meatpacking plant. He wrote it to ignite a socialist movement on behalf of America’s workers.  Chemistry Bureau Chief Harvey Wiley ("Crusading Chemist") recruited a group of young men into “the Poison Squad.” The squad volunteers ingested formaldehyde, boric acid, and other food colorings and preservatives in concentrated form.

Pure Food and Drugs Act of 1906  Food and Drugs Act is passed by Congress

on June 30 and signed by President Theodore Roosevelt.  It prohibited interstate commerce in misbranded and adulterated foods, drinks and drugs.

Mrs. Winslow’s Soothing Syrup for teething and colicky babies, unlabeled yet laced with morphine, killed many infants. 1912 Congress enacted the Sherley Amendment, which prohibits labeling medicines with false therapeutic claims intended to defraud the purchaser; a standard difficult to prove.

Elixir Sulfanilamide  Elixir Sulfanilamide is a sulfa drug (antibiotic) released

in 1937 in liquid form without prior toxicity testing of its solvent. The solvent diethylene glycol, used today as automotive antifreeze, caused the death of 107 people, mostly children. The chemist who created the elixir committed suicide.  The “Elixir Sulfanilamide tragedy” prompted the passage of the Food, Drug, and Cosmetic Act of 1938.

Food, Drug, and Cosmetic Act  Passed after the Elixir Sulfanilamide tragedy,

the required pharmaceutical manufacturers to submit a New Drug Application to prove the drugs’ safety.

Thalidomide  In 1957, a West German pharmaceutical manufacturer

introduced a new sedative, thalidomide, which alleviated the symptoms of morning sickness in women during the first trimester of pregnancy.

 In 1962, the drug was sold in forty-six countries, it

became clear that thalidomide damaged the fetus or caused stillbirth. Thousands of newborn babies were found to have truncated limbs that resemble flippers.

Kefauver-Harris Amendments  “Thalidomide babies” became a bludgeon for urging

stronger government action.

 The Kefauver-Harris Amendments authorized the

FDA to require drug companies to conduct and submit tests determining safety and efficacy.

Steps from Test Tube to New Drug Application Review  Preclinical (animal) testing.  An investigational new drug application (IND)

outlines what the sponsor of a new drug proposes for human testing in clinical trials.  Phase 1 studies (typically involve 20 to 80 people).  Phase 2 studies (typically involve a few dozen to about 300 people).  Phase 3 studies (typically involve several hundred to about 3,000 people).

Steps from Test Tube to New Drug Application (NDA) Review  Submission of an NDA is the formal step asking the FDA to     

consider a drug for marketing approval. After an NDA is received, the FDA has 60 days to decide whether to file it so it can be reviewed. If the FDA files the NDA, an FDA review team is assigned to evaluate the sponsor's research on the drug's safety and effectiveness. The FDA reviews information that goes on a drug's professional labeling (information on how to use the drug). The FDA inspects the facilities where the drug will be manufactured, as part of the approval process. FDA reviewers will approve the application or issue a complete response letter.

Drug Approval Process  It takes on average 12 years and over US$350 million to

get a new drug from the laboratory onto the pharmacy shelf.  Once a company develops a drug, it undergoes around three and a half years of laboratory testing, before an application is made to the FDA to begin testing the drug in humans.  Only one in 1000 of the compounds that enter laboratory testing will ever make it to human testing.

Clinical Trial or Study Protocol  Protocol: A document that describes the

objective(s), design, methodology, statistical considerations, and organization of a trial.

 The protocol usually also gives the background and

rationale for the trial.

ICH E9 Statistical Principles for Clinical Trials  International Conference on Harmonisation (ICH)  All important details of a clinical trial design and

conduct, and the principal features of its proposed statistical analysis should be clearly specified in a protocol written before the trial begins.

 Why?

Bias  The term bias describes the systematic tendency of

any factors associated with the design, conduct, analysis, and interpretation of the results of clinical trials to make the estimate of a treatment effect deviate from its true value.

 The presence of bias may seriously compromise the

ability to draw valid conclusions from clinical trials.

Experimental Design / Hypothesis Testing Protocol and Statistical Analysis Plan components:  Statement of hypotheses and assumptions  What data will be collected and how often  What test statistic(s) and confidence level will be used in analysis

Design Techniques to Avoid Bias  The most important design techniques for avoiding

bias in clinical trials are blinding and randomization.

 Most such trials follow a double-blind approach, so

that no one involved in the conduct of the trial is aware of the specific treatment allocated to any particular subject.

Randomization  Randomization introduces a deliberate

element of chance into the assignment of treatments to subjects in a clinical trial.

Statistical Test of Hypothesis  We know that the statistic is most likely not going to

give us the exact value of the parameter, but we want to know if it is just due to chance or to something else.

Statistical Test of Hypothesis Null hypothesis, Ho

- the observed difference is due to chance. Ex: mean of trt A = mean of trt B

Alternative hypothesis, Ha

- the observed difference is real. Ex: mean of trt A ≠ mean of trt B

Test of Hypothesis, contin. Test Statistic, TS

- numerical calculation used to measure the difference between the observed and expected (as defined by Ho)

Rejection Region, RR

- sets acceptable range of TS (based on alpha, sample size, distribution)

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Test of Hypothesis, contin.  Conclusion

- if TS is outside of RR, then reject Ho and accept Ha.

 - if TS is not outside of RR, then cannot reject Ho.  Note: we do not accept the Ho, because the Ho may

really be false, but we must live with it until we can disprove it.

Reject Ho Ho is True Ho is False

Don’t Reject Ho

Reject Ho

Don’t Reject Ho

Ho is True

Type I error

OK

Ho is False

OK

Type II error

 Probability of a Type I error = α (alpha)

= Pr(say there is a diff. when there isn’t)

 Probability of a Type II error = β (beta)

=Pr(say there is not a diff. when there is)

* Alpha (α) is set prior to analysis. ∗ α = 0.05 is typical. ∗ α will be increased by multiple comparisons, interim

analyses, etc.

* Power = 1 - β. * Power > 0.80 is typical. ∗ β is affected by std dev, n (sample size), and the size of

the difference that you are trying to detect.

P-value  P-value = probability of getting a value further away

from the population parameter than the sample statistic.

Test Conclusions  If p-value < α (significance level), then reject Ho and

say that there is a difference.

 If p-value > α , then cannot reject Ho; should state that

there is insufficient evidence to say that there is a difference. Post-study power should be calculated (want power >0.8 to avoid Type II error).

Experimental Design  Pre-experimental evaluation of potential outcomes  Define objective

Quantify the objective

 Decide on active control / placebo controls / historical

controls, ...

Sample Size  estimate of variability (std dev)  study design (1 vs. 2 tailed)  alpha (0.05)  power (0.80)  # of treatment groups  delta = how far apart 2 groups can get before they are

declared “different”

When confronted with results of a study, ask 1) were the samples randomly drawn? 2) was the study designed properly? 3) were enough patients studied? 4) were the proper methods of analysis used?

When designing an experiment, be sure 

1) to define and quantify your objective 2) to use random sampling 3) to apply appropriate study designs 4) to apply proper methods of analysis

Current challenges in the Pharma Industry 

Shortening time to approval



Identifying clinically meaningful endpoints and criteria for treatment effectiveness



Handling missing values



Dealing with global environments, including different regulatory requirements



Reimbursement based on cost-effectiveness

Challenges 

All of these have implications on how statistics have evolved, and continue to evolve, in the drug industry

“Always do right. This will gratify some people, and astonish the rest.” --- Mark Twain